18 resultados para Multiple sequence alignment


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Background Simple Sequence Repeats (SSRs) are widely used in population genetic studies but their classical development is costly and time-consuming. The ever-increasing available DNA datasets generated by high-throughput techniques offer an inexpensive alternative for SSRs discovery. Expressed Sequence Tags (ESTs) have been widely used as SSR source for plants of economic relevance but their application to non-model species is still modest. Methods Here, we explored the use of publicly available ESTs (GenBank at the National Center for Biotechnology Information-NCBI) for SSRs development in non-model plants, focusing on genera listed by the International Union for the Conservation of Nature (IUCN). We also search two model genera with fully annotated genomes for EST-SSRs, Arabidopsis and Oryza, and used them as controls for genome distribution analyses. Overall, we downloaded 16 031 555 sequences for 258 plant genera which were mined for SSRsand their primers with the help of QDD1. Genome distribution analyses in Oryza and Arabidopsis were done by blasting the sequences with SSR against the Oryza sativa and Arabidopsis thaliana reference genomes implemented in the Basal Local Alignment Tool (BLAST) of the NCBI website. Finally, we performed an empirical test to determine the performance of our EST-SSRs in a few individuals from four species of two eudicot genera, Trifolium and Centaurea. Results We explored a total of 14 498 726 EST sequences from the dbEST database (NCBI) in 257 plant genera from the IUCN Red List. We identify a very large number (17 102) of ready-to-test EST-SSRs in most plant genera (193) at no cost. Overall, dinucleotide and trinucleotide repeats were the prevalent types but the abundance of the various types of repeat differed between taxonomic groups. Control genomes revealed that trinucleotide repeats were mostly located in coding regions while dinucleotide repeats were largely associated with untranslated regions. Our results from the empirical test revealed considerable amplification success and transferability between congenerics. Conclusions The present work represents the first large-scale study developing SSRs by utilizing publicly accessible EST databases in threatened plants. Here we provide a very large number of ready-to-test EST-SSR (17 102) for 193 genera. The cross-species transferability suggests that the number of possible target species would be large. Since trinucleotide repeats are abundant and mainly linked to exons they might be useful in evolutionary and conservation studies. Altogether, our study highly supports the use of EST databases as an extremely affordable and fast alternative for SSR developing in threatened plants.

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BACKGROUND AND OBJECTIVES Multiple-breath washout (MBW) is an attractive test to assess ventilation inhomogeneity, a marker of peripheral lung disease. Standardization of MBW is hampered as little data exists on possible measurement bias. We aimed to identify potential sources of measurement bias based on MBW software settings. METHODS We used unprocessed data from nitrogen (N2) MBW (Exhalyzer D, Eco Medics AG) applied in 30 children aged 5-18 years: 10 with CF, 10 formerly preterm, and 10 healthy controls. This setup calculates the tracer gas N2 mainly from measured O2 and CO2concentrations. The following software settings for MBW signal processing were changed by at least 5 units or >10% in both directions or completely switched off: (i) environmental conditions, (ii) apparatus dead space, (iii) O2 and CO2 signal correction, and (iv) signal alignment (delay time). Primary outcome was the change in lung clearance index (LCI) compared to LCI calculated with the settings as recommended. A change in LCI exceeding 10% was considered relevant. RESULTS Changes in both environmental and dead space settings resulted in uniform but modest LCI changes and exceeded >10% in only two measurements. Changes in signal alignment and O2 signal correction had the most relevant impact on LCI. Decrease of O2 delay time by 40 ms (7%) lead to a mean LCI increase of 12%, with >10% LCI change in 60% of the children. Increase of O2 delay time by 40 ms resulted in mean LCI decrease of 9% with LCI changing >10% in 43% of the children. CONCLUSIONS Accurate LCI results depend crucially on signal processing settings in MBW software. Especially correct signal delay times are possible sources of incorrect LCI measurements. Algorithms of signal processing and signal alignment should thus be optimized to avoid susceptibility of MBW measurements to this significant measurement bias.

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Multiple osteochondromas (also called hereditary multiple exostoses) is an autosomal dominant disorder characterized by multiple cartilaginous tumors, which are caused by mutations in the genes for exostosin-1 (EXT1) and exostosin-2 (EXT2). The goal of this study was to elucidate the genetic alterations in a family with three affected members. Isolation of RNA from the patients' blood followed by reverse transcription and PCR amplification of selected fragments showed that the three patients lack a specific region of 90 bp from their EXT1 mRNA. This region corresponds to the sequence of exon 8 from the EXT1 gene. No splice site mutation was found around exon 8. However, long-range PCR amplification of the region from intron 7 to intron 8 indicated that the three patients contain a deletion of 4318 bp, which includes exon 8 and part of the flanking introns. There is evidence that the deletion was caused by non-homologous end joining because the breakpoints are not located within a repetitive element, but contain multiple copies of the deletion hotspot sequence TGRRKM. Exon 8 encodes part of the active site of the EXT1 enzyme, including the DXD signature of all UDP-sugar glycosyltransferases. It is conceivable that the mutant protein exerts a dominant negative effect on the activity of the EXT glycosyltransferase since it might interact with normal copies of the enzyme to form an inactive hetero-oligomeric complex. We suggest that sequencing of RNA might be superior to exome sequencing to detect short deletions of a single exon.